Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County.
Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.
","abstract_html":"<p>Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County.</p> <p>Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.</p>","abstract_has_math":false,"creators":["Oris, William Nathan"],"institution":null,"degree_name":"Master of Science","degree_level":null,"degree_discipline":"Department of Geography and Geology","degree_department":null,"school":null,"contributors":["Dr. Jun Yan (Director), Dr. David Keeling, Dr. Stuart Foster, Dr. Kevin Cary"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-12-01T08:00:00Z","date_published":"2011-12-01T08:00:00Z","updated_at":"2026-07-24T06:08:09Z","subjects":["GIS","urban transportation","Kentucky traffic fatalities","traffic safety","urban planning","FARS","Applied Statistics","Categorical Data Analysis","Geographic Information Sciences","Geography","Physical and Environmental Geography","Public Affairs","Public Affairs, Public Policy and Public Administration","Transportation"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wku.edu/theses/1119","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Jun Yan (Director), Dr. David Keeling, Dr. Stuart Foster, Dr. Kevin Cary"]},{"key":"dc:creator","label":"Author","values":["Oris, William Nathan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Department of Geography and Geology"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["GIS","urban transportation","Kentucky traffic fatalities","traffic safety","urban planning","FARS","Applied Statistics","Categorical Data Analysis","Geographic Information Sciences","Geography","Physical and Environmental Geography","Public Affairs","Public Affairs, Public Policy and Public Administration","Transportation"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wku.edu/theses/1119"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County.
Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.
"]},{"key":"dc:title","label":"Title","values":["Spatial Analysis of Fatal Automobile Crashes in Kentucky"]}]}],"canonical_facts":{"dc:contributor":["Dr. Jun Yan (Director), Dr. David Keeling, Dr. Stuart Foster, Dr. Kevin Cary"],"dc:creator":["Oris, William Nathan"],"dc:description.abstract":["Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County.
Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.
"],"dc:identifier":["https://digitalcommons.wku.edu/theses/1119"],"dc:subject":["GIS","urban transportation","Kentucky traffic fatalities","traffic safety","urban planning","FARS","Applied Statistics","Categorical Data Analysis","Geographic Information Sciences","Geography","Physical and Environmental Geography","Public Affairs","Public Affairs, Public Policy and Public Administration","Transportation"],"dc:title":["Spatial Analysis of Fatal Automobile Crashes in Kentucky"],"dc:type":["Thesis"],"thesis:degree_discipline":["Department of Geography and Geology"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T06:08:09Z"}